Triple
T25684941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2011 Census of India |
E644040
|
entity |
| Predicate | literacyRateOverall |
P163695
|
FINISHED |
| Object | 74.04 percent |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 74.04 percent | Statement: [2011 Census of India, literacyRateOverall, 74.04 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literacyRateOverall Context triple: [2011 Census of India, literacyRateOverall, 74.04 percent]
-
A.
femaleLiteracyRate
Indicates the proportion of females in a population who can read and write at a specified minimum level of proficiency.
-
B.
maleLiteracyRate
Indicates the percentage of males in a given population who can read and write at a specified minimum level of proficiency.
-
C.
literacyStatus
Indicates whether an entity possesses the ability to read and write, or its level of literacy.
-
D.
typeOfLiteracy
Indicates the specific kind or category of literacy (e.g., digital, financial, media) that characterizes an entity’s literacy skills or practices.
-
E.
literacyRequirementAdministeredBy
Indicates that the administration or enforcement of a literacy requirement is carried out by a specified agent or authority.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e77e8046888190b07ffa58c7e2c37a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6397b64f881909d811225e57aac5e |
completed | May 2, 2026, 5:50 p.m. |
| PD | Predicate disambiguation | batch_69f63706b6008190993577193c85ff50 |
completed | May 2, 2026, 5:40 p.m. |
| PDg | Predicate description generation | batch_69f638d029148190877c103f0eeaf147 |
completed | May 2, 2026, 5:48 p.m. |
Created at: April 21, 2026, 8:06 p.m.